Work environment
Would you like to actively contribute to keeping our customers around the world mobile — throughout the entire product life cycle of our Genuine Parts? Do you enjoy improving processes, working with data, and creating real impact? Then you’ve come to the right place! In our After Sales Quality – Supplier Relations & Analytics team, we support the Group in ensuring product compliance, sustainably improving processes and parts quality, and reducing risks and costs in the long term. We look forward to receiving your application!
Possible tasks within this role
- Contributing to projects focused on process and parts quality optimization in After Sales and taking ownership of sub‑projects
- Creating presentations, analyses, and dashboards (PowerPoint, Excel, Power BI)
- Analyzing large volumes of data, preparing evaluations, and deriving improvement measures
- Maintaining and linking databases as well as supporting the development of new reporting structures
- Supporting the further development of concepts, processes, and KPIs along the After Sales quality chain
Qualification requirements
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Master’s students (or Bachelor’s students with at least 90 ECTS) in a business or technical field (e.g., industrial engineering or comparable programs)
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Good to very good academic performance; at least 12 months remaining study duration is advantageous
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Excellent MS Office skills (especially Excel & PowerPoint)
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Initial experience with Power tools & reporting tools (e.g., Power BI, Power Apps) as well as data analysis is desirable
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Basic knowledge of VBA or other programming languages is a plus
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Interest in process optimization, quality, and data‑driven work, as well as a structured, independent, and solution‑oriented working style
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English language level B1
The following documents must be submitted with your application
- Curriculum Vitae
- Current certificate of enrolment
- Current transcript of records
- Work permit for non-EU citizens
Keywords
Quality Management, Data Visualization, Supply Chain Management, Failure Analysis, Business Analytics, Database Management, Root‑Cause Analysis
Contact person for this posting: Maximilian Kaeding